Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Analyse and enhance risk models for commodities using Python.
- Company: Leading energy trading firm with a focus on innovation.
- Benefits: Autonomy, direct access to senior stakeholders, and impactful work.
- Why this job: Make a real impact in the dynamic world of commodities trading.
- Qualifications: Experience in commodities, strong modelling skills, and Python proficiency.
- Other info: No CV needed to apply; just bring your passion and skills!
The predicted salary is between 36000 - 60000 £ per year.
Want to work at one of the most successful energy trading firms? Here you’ll take on a broad mix of quantitative risk and analytics work across a wide range of commodities products. If you enjoy variety and real impact, this is the kind of role that offers both.
You’ll stay hands-on - building and enhancing risk models in Python, working closely with traders, risk managers and the wider analytics teams, and shaping how the firm measures and manages risk. Reporting directly to the Lead Quant Risk, you’ll have genuine autonomy and access to senior stakeholders who value strong technical judgement.
Day to day, you’ll be improving and developing the firm’s core risk metrics, ensuring they’re accurate, scalable and aligned with how the business trades. It’s a role where your technical depth and market understanding will genuinely influence decision-making.
You’ll need a background in commodities, alongside strong modelling and risk metrics (VAR, CAR, PFE, Liquidity at Risk) and Python skills.
If you want to join a firm pushing the future of commodities, apply or get in touch directly at megan@saragossa.io. No up-to-date CV required.
Quant Risk Analyst - Commodities employer: Saragossa
Contact Detail:
Saragossa Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quant Risk Analyst - Commodities
✨Tip Number 1
Network like a pro! Reach out to current employees at the firm on LinkedIn or through mutual connections. A friendly chat can give you insider info and might just get your foot in the door.
✨Tip Number 2
Show off your skills! If you’ve got experience with Python and risk metrics, consider creating a small project or analysis to showcase your abilities. Share it during interviews to demonstrate your hands-on approach.
✨Tip Number 3
Prepare for the interview by brushing up on your commodities knowledge and risk modelling techniques. Be ready to discuss how you would improve risk metrics and align them with trading strategies.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who take that extra step to connect directly.
We think you need these skills to ace Quant Risk Analyst - Commodities
Some tips for your application 🫡
Show Your Quant Skills: Make sure to highlight your experience with quantitative risk and analytics in your application. We want to see how you've tackled similar challenges in the past, especially with commodities products.
Be Hands-On: We love candidates who are hands-on! Share examples of how you've built or enhanced risk models in Python. This will show us that you’re not just theoretical but can apply your skills in real-world scenarios.
Tailor Your Application: Don’t just send a generic application. Tailor it to reflect your understanding of our firm and the role. Mention specific risk metrics like VAR or PFE that you’ve worked with, and how they relate to our business.
Reach Out Directly: If you have questions or want to make a personal connection, don’t hesitate to reach out to us at megan@saragossa.io. We’re all about open communication and would love to hear from you!
How to prepare for a job interview at Saragossa
✨Know Your Commodities
Make sure you brush up on your knowledge of commodities markets. Understand the key products and how they are traded. This will not only help you answer questions confidently but also show your genuine interest in the role.
✨Showcase Your Python Skills
Be prepared to discuss your experience with Python, especially in relation to building risk models. You might even be asked to solve a problem on the spot, so practice coding challenges that relate to quantitative risk analysis.
✨Understand Risk Metrics Inside Out
Familiarise yourself with key risk metrics like VAR, CAR, and Liquidity at Risk. Be ready to explain how these metrics are calculated and their importance in trading decisions. This will demonstrate your technical depth and understanding of risk management.
✨Engage with Stakeholders
Since you'll be working closely with traders and risk managers, think about how you can communicate complex ideas clearly. Prepare examples of how you've successfully collaborated with different teams in the past, as this will highlight your ability to influence decision-making.